Attribution Theory and Online Learning

In my earlier posts, I discussed the ESPRI and the factors associated with predicting student success. My research is looking to examine how we can use the ESPRI to help improve student performance in online courses by addressing areas of weakness in a student’s “soft” skill set. To recap, the four areas covered in the ESPRI are technology self-efficacy, achievement beliefs, organizational skills, and academic risk-taking. In this post, I will discuss ways to intervene with the first two.

To begin, some definitions. Self-efficacy relates to the beliefs about successfully performing academic tasks, while self-concept is the knowledge and perceptions about one’s own academic achievement (Ferla et al., 2009). Attribution theory (Weiner, 1992) relates to the reasons that students attribute academic outcomes, which fall into three categories: locus of control (i.e., are the reasons internal or external to the learner?), stability (i.e., is the reason temporary or lasting?), and controllability (i.e., how it relates to learner persistence).

Simply put, the more the student believes that he or she is in control of the outcome, the more likely the student is to persist, maintain motivation, and change behaviors to improve learning.  Since a large population of online learners are taking courses for credit recovery, or are in an alternative setting due to being unsuccessful in a traditional school, changing mindsets is critical.

But how do you teach that? Can you teach that? Studies have been somewhat scarce and mixed. Walden and Ramey (1983) found that high-risk students who participated in a long-term intervention on internalizing control did see improvement in academic achievement. Robertson’s (2000) review of attribution retraining studies found mixed results, and based on the review recommended that attribution retraining interventions should include additional steps to ensure positive results. In other words, simply telling students to internalize attributions may lead to decreased motivation if they are still unsuccessful. Robertson suggested the inclusion of other learning strategies; thus, if the student is not successful, it could be viewed as a mistake related to the strategy rather than overall ability. Finally, Chodkiewicz and Boyle (2014) provided an overall critique of attribution studies as they relate to education, stating that much of the literature from the field of psychology is conducted in clinical settings, with little taking place in the classroom.

Regarding my current research with online learning, my efforts seem to be in line with Robertson’s recommendations, as we are looking to tackle multiple strategies and not simply student belief systems.


Chodkiewicz, A. R., & Boyle, C. (2014). Exploring the contribution of attribution retraining to student perceptions and the learning process. Educational Psychology in Practice, 30(1), 78-87.

Ferla, J., Valcke, M., & Cai, Y. (2009). Academic self-efficacy and academic self-concept: Reconsidering structural relationships. Learning and Individual Differences, 19(4), 499-505.

Robertson, J. S. (2000). Is Attribution Training a Worthwhile Classroom Intervention For K–12 Students with Learning Difficulties? Educational Psychology Review, 12(1), 111-134.

Walden, T. A., & Ramey, C. T. (1983). Locus of control and academic achievement: Results from a preschool intervention program. Journal of Educational Psychology, 75(3), 347-358.

Weiner, B. (1992). Human Motivation: Metaphors, Theories and Research. Newbury Park, CA: Sage Publications.

MOOC's, learning and theoretical assumptions

The latest buzzword in educational technology are MOOC’s – Massive Open Online Courses – gaining interest in higher education with numerous articles published on their potential for opening access to higher education for those who cannot currently afford it. A recent search of peer-reviewed publications on MOOC’s returned almost 750 results. One key aspect of MOOC’s that is especially attractive is their cost, with MIT, for example, offering a variety of MOOC’s free and Coursera also offering them as well.    

Ferdig (2013) asks a critical question regarding MOOC's: “under what conditions do (insert specific type of MOOC) work?” (p. 5). He suggests that there is still insufficient research to support a clear or convincing answer to this question. Ferdig, Pytash, Merchant & High (2014) report on their experiences with a MOOC targeted at teachers and 21^st century learning, identifying three types of participants: lurkers, who observed but did not actively participate; passive participants, who did a minimal amount of work required to complete the course; and active participants, who were highly engaged in the course.  

An article by Koller, Ng, Do and Chen (2013) explores the issue of retention by students in MOOC’s. The basis for the authors’ argument is that we need to reconsider what we mean by “retention” in light of students’ intentions for enrolling. The evidence provided so far suggests that few students are retained or complete assessments associated with MOOC's, but the author’s argue that student intention should be a filter through which we interpret the low completion evidence. Is this a valid argument, given what we know about learning?

A criticism of Koller, Ng, Do and Chen’s argument is their implicit assumption about the nature of learning that drives their claims regarding MOOC's. Like Ferdig, Pytash, Merchant and High, the authors identify MOOC learners using three categories: passive participants, active participants, and community contributors. They provide analysis of these types using assessments, participation and explore relationships between these groups related to: (a) lecture watching and assignment completion, (b) lecture watching and quiz taking, and (c) quiz taking and assignment completion.

These types of MOOC activities and assessments raise questions about the instruction and learning that occurs in this and other MOOC studies. Questions include: how active or engaged are students in learning? How substantive is their learning as a result of their participation? What is it they are learning? Implicit in some of the MOOC studies are assumptions about learning that could be considered as behaviorist, drawing on the work of Skinner and Watson.  

Behaviorist learning theories make assumptions about learning as passive viewing and often include assessments of learning as recall of factual information using known-answer tests or quizzes. These assumptions stand in contrast to theories of learning generally accepted amongst educational psychologists that look beyond recall and memorization into other areas, including the nature of expertise.

Bransford, Brown & Cocking (2001), for example, provide a synthesis of research on learning and expertise, identifying aspects of effective learning communities: learner-centered environments that consider existing knowledge, skill and beliefs learners bring; knowledge-centered pedagogy that recognizes that learning is (or should be) focused on understanding and adaptive expertise; assessments that include formal and informal feedback on understanding, not memorization, to encourage and reward “meaningful learning;” and incorporation of social environments where individuals learn from each other via active, constructive participation.

Clara & Barbera (2013) offer a critique of MOOC's based on the implicit theoretical perspective of their designers when compared with social-cultural learning theory. “The conclusion of this discussion is that, taken from a psychological point of view, connectivism, as currently formulated, should be abandoned as a learning theory and as a theoretical guide for pedagogy in MOOCs and in Web 2.0 environments in general.” (p. 134).

Bates (August 5, 2012) offers a similar criticism about MOOCs: “… teaching methods used by most Coursera courses so far are based on a very old and outdated behaviorist pedagogy, relying primarily on information transmission, computer marked assignments and peer assessment.” MOOC’s, as currently defined and implemented, may disregard or ignore what we know about the nature of learning and expertise, which could ultimately undermine their value and contribution to higher education.

 “The challenge in a MOOC is whether the levels of support by facilitators and other learners and the affordances of a complex emerging learning environment will align and aid participants in such sense-making, and whether the openness, diversity, and interactivity of MOOCs aids participants on their personalized learning journey.” Kop, Fournier & Mak, 2011, p. 88.

References

Bates, T. (August 5, 2012). What’s right and what’s wrong about Coursera-style MOOCs?  http://www.tonybates.ca/2012/08/05/whats-right-and-whats-wrong-about-coursera-style-moocs/

Clara, M., and Barbera, E. (2013). Learning online: Massive open online courses (MOOCs), connectivism, and cultural psychology. Distance Education, 34(1), 129-136.  

Ferdig, R. (2013). What Massive Open Online Courses have to offer K-12 teachers and students? Michigan Virtual Learning Research. Available online at: http://www.mvlri.org

Ferdig, R.E., Pytash, K.E., Merchant, W., & Nigh, J. (2014). Findings and reflections from the K-12 Teaching in the 21^st century MOOC. Michigan Virtual Learning Research. Available online at: http://www.mvlri.org

How people learn: Brain, mind, experience and school (2001). Bransford, J.D., Brown, A.L., & Cocking, R.R. (Eds.). The National Academies Press, open book available online at: http://www.nap.edu/openbook.php?isbn=0309070368

Koller, D., Ng, A., Do, C. & Chen, Z. (2013, June 3). Retention and Intention in MOOC: In Depth, EDUCAUSE Review. Retrieved on April 3, 2014 from: http://www.educause.edu/ero/article/retention-and-intention-massive-open-online-courses-depth-0

Kop, R., Fournier, H., & Mak, J.S.F. (2011). Pedagogy of abundance or pedagogy to support human beings? Participant support on Massive Open Online Courses. The International Review of Research in Open and Distance learning, 12(7), 74-93. 

Andy